Public record
Software health reportschema 0.12.0 · metrics 2.10.0 · 2026-07-18 00:26 UTC

greenbone / greenbone-feed-sync

Tool for downloading the Greenbone Community Feed

PythonGPL-3.0★ 30 stars⑂ 15 forkssince Dec 2022View on GitHub ↗

greenbone/greenbone-feed-sync holds a health index of 86 out of 100, placing it in the Excellent band. It scores highest on Vitality (94/100) and lowest on AI Readiness (39/100). It was last updated 2 days ago. 2 contributors account for most of its recent work.

86
overall / 100
Excellent

Software health index

Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean, calibrated against the distribution of the public record so bands carry percentile meaning; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At Risk ceiling of 34.

86
Exceptional93-100The record's top tier (≈ top 5%); essentially all checked criteria met
Excellent80-92Strong across the board; minor gaps
Good65-79Healthy; gaps are limited and manageable
Moderate50-64Acceptable with notable gaps; review recommended
Weak35-49Material weaknesses across several areas
At Risk20-34Significant weaknesses; adoption warrants caution
Critical1-19Severe problems (abandoned, single-maintainer, no hygiene)
VitalityCommunity &AdoptionSustainability &GovernanceEngineeringQualitySecurityAI Readiness

Score profile

Each axis is a category. The shape matters more than the average — a healthy subject fills the whole shape, while a spike-and-crater profile means strength in one dimension is masking risk in another.

The weighted overall 72 is calibrated to 86 on the published index scale (record calibration 2026-08-02).

Ownership

GreenboneOrganization
1,310 followers68 public repossince Sep 2017

This repository is backed by an organization — shared, accountable stewardship that can outlive any single maintainer.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIgreenbone-feed-sync25.4.1-232 days ago

Metrics by category

Vitality

Is the project alive — is code being written and are releases shipping?

94Exceptional · 21% of overall
How it's scored
36/36Push recencylast push 2 days ago
28.4/36Commit cadence41/52 weeks with commits
18/18Commit volume104 commits in the last year
10/10OpenSSF Scorecard: Maintained22 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year104
human_commit_share
days_since_last_push2
active_weeks_last_year41

Release discipline

98Exceptional
How it's scored
27/27Ships releases26 releases published
36/36Release recencylatest release 2 days ago
27/27Release cadencea release every ~31.9 days
8/10OpenSSF Scorecard: Signed-Releases5 out of the last 5 releases have a total of 5 signed artifacts.
Inputs used
releases_count26
latest_release_tagv25.4.1
releases_from_tagsno
days_since_latest_release2
mean_days_between_releases31.9

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

46Weak · 17% of overall
How it's scored
23.7/60Stars30 stars
9.6/25Forks15 forks
3.3/15Watchers5 watchers
Inputs used
forks15
stars30
watchers5
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (GPL-3.0)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services
has_pull_request_templateyes

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

80Excellent · 23% of overall
How it's scored
25.2/54Bus factor2 contributor(s) cover half of all commits
11.9/22.5Commit distributiontop contributor authored 47% of commits
13.5/13.5Contributor breadth15 contributors
3/10OpenSSF Scorecard: Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
Inputs used
bus_factor2
contributors_sampled15
top_contributor_share0.472
How it's scored
36/42Issue resolution86% of issues closed
26.3/30PR acceptance310/354 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
7.5/15OpenSSF Scorecard: Code-ReviewFound 8/14 approved changesets -- score normalized to 5
Inputs used
merged_prs310
open_issues1
closed_issues6
prs_merged_7d
prs_decided_7d
prs_merged_30d
prs_decided_30d
issue_closed_ratio0.857
closed_unmerged_prs44
first_time_authors_30d
first_time_prs_merged_30d
first_time_prs_decided_30d
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domainverified-domain status not read for this organization
22.4/25Owner reach1,310 followers of greenbone
25/25Track record68 public repos, account ~8 yr old
Inputs used
followers1,310
owner_typeOrganization
is_verified
owner_logingreenbone
public_repos68
account_age_days3,227
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 2 days ago
20/20Version history23 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesgreenbone-feed-sync
ecosystemspypi
any_deprecatedno
min_days_since_publish2

Engineering Quality

Are baseline engineering and documentation practices in place?

67Good · 19% of overall
How it's scored
24/24CI workflows11 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests22 out of 22 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno
How it's scored
30/30README
0/25Documentation directory
15/15Documentation / homepage sitehttps://greenbone.github.io/docs/
10/10Repository description
10/10Topics9 topics
0/10Wiki
Inputs used
topicsfeed, greenbone, greenbone-community-edition, greenbone-vulnerability-management, openvas, openvas-scanner, base, python, tooling
has_wikino
homepagehttps://greenbone.github.io/docs/
docs_sitehttps://greenbone.github.io/docs/
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?

71Good · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionno data
2.5/2.5CI-Tests22 out of 22 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
3.8/7.5Code-ReviewFound 8/14 approved changesets -- score normalized to 5
0.8/2.5Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
10/10Dangerous-Workflowno dangerous workflow patterns detected
7.5/7.5Dependency-Update-Toolupdate tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
7.5/7.5Maintained22 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
0/5Packagingno data
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
5/5SASTSAST tool is run on all commits
5/5Security-Policysecurity policy file detected
6/7.5Signed-Releases5 out of the last 5 releases have a total of 5 signed artifacts.
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate7.1
Excluded from scoring (no data or not applicable): Branch-Protection, Packaging. Remaining weights renormalized.

AI Readiness

How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight (4%): agent tooling is a real maintenance signal, but a repository with none can still reach 100/100.

39Weak · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
0/40Legible commit historyno data
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share
agent_instruction_files
agent_instruction_max_bytes
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.
How it's scored
18/18One-command bootstrapMakefile
22/22Automated tests
0/11Lint / format config
0/11Static type checking
10/10Reproducible environmentDockerfile, lockfile
0/10Demonstrated agent practiceno data
5/8Automated maintenancedependency automation configured, none observed in the sampled commits
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileyes
typed_languageno
bootstrap_filesMakefile
has_devcontainerno
has_linter_configno
typecheck_configs
agent_commit_share
toolchain_manifests
dependency_bot_commit_share0
Excluded from scoring (no data or not applicable): Demonstrated agent practice. Remaining weights renormalized.
How it's scored
0/45Type-checkable codePython without a type-check config
55/55Manageable file sizes0/14 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes39,253
source_files_sampled14
oversized_source_files0

Key facts

30GitHub stars
15contributors
104commits, last 12 months
2days since last push
26releases
2bus factor
1open issues
PyPIpackage ecosystems

More detail

OpenSSF Scorecard 7.1 / 10
7.1aggregate

Independent, tool-agnostic security assessment from the open-source OpenSSF Scorecard. Each check rewards a security practice, not a specific vendor's tool. Checks Scorecard could not determine are marked n/a and excluded from the security score (never counted as zero).Scorecard v5.5.0 · 2026-07-18 00:26 UTC

10Binary-Artifactsno binaries found in the repo
n/aBranch-Protectioninternal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md
10CI-Tests22 out of 22 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
5Code-ReviewFound 8/14 approved changesets -- score normalized to 5
3Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained22 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
n/aPackagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
10SASTSAST tool is run on all commits
10Security-Policysecurity policy file detected
8Signed-Releases5 out of the last 5 releases have a total of 5 signed artifacts.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 3
RegistryPackageVersion constraintManifest
PyPIrich>=13.2.0pyproject.toml
PyPItomli>=2.0.1pyproject.toml
PyPIshtab>=1.6.5pyproject.toml
All dependencies 37

Full resolved dependency set from the GitHub dependency graph: 3 direct and 34 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIrich15.0.0direct
PyPIshtab1.8.1direct
PyPItomli2.4.1direct
PyPIanyio4.13.0indirect
PyPIautohooks26.2.0indirect
PyPIautohooks-plugin-mypy23.10.0indirect
PyPIautohooks-plugin-ruff25.3.1indirect
PyPIcertifi2026.2.25indirect
PyPIcolorama0.4.6indirect
PyPIcolorful0.5.8indirect
PyPIcoverage7.13.5indirect
PyPIexceptiongroup1.3.1indirect
PyPIgit-cliff2.13.1indirect
PyPIgreenbone-feed-sync25.4.1.dev1indirect
PyPIh110.16.0indirect
PyPIh24.3.0indirect
PyPIhpack4.1.0indirect
PyPIhttpcore1.0.9indirect
PyPIhttpx0.28.1indirect
PyPIhyperframe6.1.0indirect
PyPIidna3.15indirect
PyPIlibrt0.8.1indirect
PyPIlxml6.1.0indirect
PyPImarkdown-it-py4.0.0indirect
PyPImdurl0.1.2indirect
PyPImypy1.20.0indirect
PyPImypy-extensions1.1.0indirect
PyPIpackaging26.0indirect
PyPIpathspec1.0.4indirect
PyPIpontos26.5.0indirect
PyPIpygments2.20.0indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIruff0.15.9indirect
PyPIsemver3.0.4indirect
PyPIsix1.17.0indirect
PyPItomlkit0.14.0indirect
PyPItyping-extensions4.15.0indirect
Raw JSON report machine-readable

Feedback

Spotted something off in this report, or have thoughts to share? Wrong measurements, missed tooling, ideas, questions — anything is welcome. Every message is read and gets a response.

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Scores are signals, not warranties. They reflect publicly visible practices on GitHub — not a code audit, and not a security guarantee.

Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v2.10.0, schema v0.12.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statisticsPyPI.